1,530 research outputs found
Low-Complexity Explicit MPC Controller for Vehicle Lateral Motion Control
No full textWe consider the problem of controlling the vehicle lateral motion in highway scenarios while guaranteeing safety. We propose a solution consisting of a Low-Complexity Explicit Model Predictive Controller (LC-EMPC), where the lateral deviation from the desired path is hard constrained according to prescribed bounds. The robust satisfaction of such safety constraints can be achieved by imposing the terminal state to enter a Robust Invariant Set (RIS), which is known to result into a potentially high number of additional constraints, thus increasing the computational complexity of the controller. Our controller, instead, relies on recent results on the calculation of low-complexity RIS to significantly reduce the number of constraints in the MPC controller. Simulation results show that the designed controller is able to meet the desired objectives with highly reduced complexity
Full-complexity characterization of control-invariant domains for systems with uncertain parameter dependence
No full textThis letter proposes an algorithm to find a robust control invariant (RCI) set of desired complexity and the associated linear, state-feedback control law. The candidate RCI set is restricted to be symmetric around the origin. The algorithm is applicable to rational parameter dependent systems with bounded additive disturbance. The system constraints are framed as simple affine inequalities whereas the invariance condition as a set of sufficient LMI conditions. The proposed iterative algorithm is guaranteed to be recursively feasible and converge to some stationary point
Restricted-Complexity Characterization of Control-Invariant Domains with Application to Lateral Vehicle Dynamics Control
No full textThis paper proposes two algorithms to find a restricted-complexity robust control invariant (RCI) set along with a state-feedback gain. These algorithms are applicable to a linear system with additive disturbances subject to found polytopic state and input constraints. The RCI set is a polytope with restricted complexity, symmetric around the origin. Using a state transformation, novel LMI conditions are derived for the system constraints and invariance condition. Moreover, a new approach is proposed to iteratively increase the volume of the computed RCI set. The effectiveness of the proposed algorithm is illustrated by using lateral vehicle dynamics control example
Module 3 - Short Fiber Reinforced Composite 3D Printing
No full textThis video workshop, published by Motlow State Community College, is part of an eight-video series from the SMARTT Project. The video provides two presentations on additive manufacturing from PhD candidates at Tennessee Technological University. The first presentation is led by Ankit Gupta. Gupta demonstrates how professionals could make short carbon fiber reinforced filaments using Filabot extruders. Gupta provides an introduction to Fiber Reinforced Additive Manufacturing (FRAM) and information on experiments. The second presentation is led by Seymur Hasanov. Hasanov discusses multi-material printing technology, specifically Z-Morph printers, and considers their materials, methods, and interface strength. Dr. Ismail Fidan introduces and concludes the video. The video recording runs 33:33 minutes in length
Computation of low-complexity control-invariant sets for systems with uncertain parameter dependence
No full textThis paper considers the problem of computing a low-complexity robust control-invariant (LC-RCI) set for uncertain systems, along with a static linear state-feedback law. The LC-RCI set, assumed to be symmetric around the origin and described by the same number of affine inequalities as twice the dimension of the state vector, is the result of an iterative procedure, where semi-definite programs (SDPs) are solved at each step. The SDPs are formulated to increase the LC-RCI volume at each step, subject to tractable reformulations of the system constraints as well as the invariance condition (in the form of standard or dilated LMIs), and a new approach to determinant maximization. The two proposed algorithms are applicable to systems with rational parameter dependence, which cannot be handled with the existing similar approaches without introducing additional conservatism
Vehicle Lateral Motion Control with Performance and Safety Guarantees
No full textThis paper explores the use of Model Predictive Control (MPC) techniques to solve vehicle lateral motion control problem on highway scenarios. In particular, the problem of autonomously driving a vehicle along a desired path is formulated, where safety constraints and performance levels must be guaranteed for all possible road curvatures within a con [pact set. Safety constraints are translated into a maximum lateral deviation and orientation error w.r.t. a desired path, while performance requirements are formulated in terms of bounded lateral acceleration and velocity. Preliminary simulation results ahoy that the designed controller is capable of delivering acceptable performance at the cost of limited online computational costs. (C) 2016, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved
Adaptive traffic signal control for developing countries using fused parameters derived from crowd-source data
Full text linkMishra, S., Singh, V., Gupta, A., Bhattacharya, D., & Mudgal, A. (2023). Adaptive traffic signal control for developing countries using fused parameters derived from crowd-source data. Transportation Letters, 15(4), 296-307. https://doi.org/10.1080/19427867.2022.2050493 ----The present work in the paper was not funded by any organization. One of the coauthor, Devanjan Bhattacharya has received funding from UKRI ESRC Impact Acceleration Grant (ES/T50189X/1), and European Union’s Horizon 2020 Research and Innovation Programme under the Marie Skłodowska-Curie COFUND Grant Agreement No. 801215: TRAIN@Ed: ‘Transnational Research And Innovation Network At Edinburgh.’Advancement of mobile technologies has enabled economical collection, storage, processing, and sharing of traffic data. These data are made accessible to intended users through various application program interfaces (API) and can be used to recognize and mitigate congestion in real time. In this paper, quantitative (time of arrival) and qualitative (color-coded congestion levels) data were acquired from the Google traffic APIs. New parameters that reflect heterogeneous traffic conditions were defined and utilized for real-time control of traffic signals while maintaining the green-to-red time ratio. The proposed method utilizes a congestion-avoiding principle commonly used in computer networking. Adaptive congestion levels were observed on three different intersections of Delhi (India), in peak hours. It showed good variation, hence sensitive for the control algorithm to act efficiently. Also, simulation study establishes that proposed control algorithm decreases waiting time and congestion. The proposed method provides an economical alternative to expensive sensing and tracking technologies.authorsversionpublishe
Read counts at multiple attenuation levels as an object localization technique using passive RFID tags
No full textRadio Frequency Technologies (RFID) are experiencing rapid development and business, retail, manufacturing and healthcare are the major application areas benefiting from it. We describe and analyze an algorithm which helps in tracking of medical equipment and personnel and patients in a Trauma Bay. We adapt the Read Count algorithm to be used at multiple attenuation levels as a localization technique. The input parameter to the algorithm is the read count value which gives a measure of number of times the back-scattered radio frequencies from passive tags has been received by the antenna. Special attention has to be given to the placement of antennas to get the optimum result. The detection of multiple tags and human occlusion are two major concerns which we have tried to solve by suing multiple horizontal antennas along with 1 vertical antenna. We have discussed the results and analysis of such a configuration and accordingly given a conclusion. The problems associated with the configuration have also been discussed which can form part of future work.M.S.Includes bibliographical referencesby Ankit Sard
Determinant Equivalence Test over Finite Fields and over Q
Full text linkThe determinant polynomial Det_n(x) of degree n is the determinant of a n x n matrix of formal variables. A polynomial f is equivalent to Det_n(x) over a field F if there exists a A in GL(n^2,F) such that f = Det_n(A * x). Determinant equivalence test over F is the following algorithmic task: Given black-box access to a f in F[x], check if f is equivalent to Det_n(x) over F, and if so then output a transformation matrix A in GL(n^2,F). In (Kayal, STOC 2012), a randomized polynomial time determinant equivalence test was given over F = C. But, to our knowledge, the complexity of the problem over finite fields and over Q was not well understood.
In this work, we give a randomized poly(n,log |F|) time determinant equivalence test over finite fields F (under mild restrictions on the characteristic and size of F). Over Q, we give an efficient randomized reduction from factoring square-free integers to determinant equivalence test for quadratic forms (i.e. the n=2 case), assuming GRH. This shows that designing a polynomial-time determinant equivalence test over Q is a challenging task. Nevertheless, we show that determinant equivalence test over Q is decidable: For bounded n, there is a randomized polynomial-time determinant equivalence test over Q with access to an oracle for integer factoring. Moreover, for any n, there is a randomized polynomial-time algorithm that takes input black-box access to a f in Q[x] and if f is equivalent to Det_n over Q then it returns a A in GL(n^2,L) such that f = Det_n(A * x), where L is an extension field of Q and [L : Q] <= n.
The above algorithms over finite fields and over Q are obtained by giving a polynomial-time randomized reduction from determinant equivalence test to another problem, namely the full matrix algebra isomorphism problem. We also show a reduction in the converse direction which is efficient if n is bounded. These reductions, which hold over any F (under mild restrictions on the characteristic and size of F), establish a close connection between the complexity of the two problems. This then leads to our results via applications of known results on the full algebra isomorphism problem over finite fields (Rónyai, STOC 1987 and Rónyai, J. Symb. Comput. 1990) and over Q (Ivanyos {et al}., Journal of Algebra 2012 and Babai {et al}., Mathematics of Computation 1990)
- …
